Ying Cheng

The Academic Ranking of World Universities

Shanghai Jiao Tong University1 has published on the Internet an Academic Ranking of World Universities that has attracted worldwide attention. Institutions are ranked according to academic or research performance and ranking indicators include major international awards, highly cited researchers in important fields, articles published in selected top journals and/or indexed by major citation indexes, and performance per capita. Methodological problems discussed here include quantitative versus qualitative evaluation, assessing research versus education, the variety of institutions, the language of publications, selection of awards, etc. Technical problems such as the definition and naming of institutions, the merging and splitting of institutions, and the search for and attribution of publications are discussed. 1. Read about this key university in China at ⟨http://www.sjtu.edu.cn/www/english/⟩.

Academic ranking of world universities using scientometrics - A comment to the "Fatal Attraction"

SummaryThe Institute of Higher Education, Shanghai Jiao Tong University published on the web the Academic Ranking of World Universities and attracted wide attentions worldwide. 60% of their criteria are based on the databases using scientometrics. They were aware of all possible technical problems, have gone through “clean up” processes and made necessary corrections. Highly cited researchers and articles published in Nature and Science were identified one by one and attributed to the correct institutions. They are confident that errors including human ones in their data are less than two percent. They will continue their ranking efforts, improve their ranking methodologies and provide more choices on the ranking lists.

A first approach to the classification of the top 500 world universities by their disciplinary characteristics using scientometrics

SummaryIn this study, the top 500 world universities are classified into 21 types according to their disciplinary characteristics using clustering method. The indicators used to represent the disciplinary characteristics of an institution are the proportion of publications in six broader disciplinary areas: Arts/Humanities & Social Sciences, Natural Sciences & Mathematics, Engineering/Technology & Computer Sciences, Life Sciences, Clinical Medicine, and Interdisciplinary & Multidisciplinary Sciences. Institutions have been classified into types of having focus in a disciplinary group, having priority in a disciplinary group, having orientation in a disciplinary group, and balanced. The distribution of different types of institutions with respect to countries and ranks are analyzed.

Examining Major Rankings According to the Berlin Principles

While the ranking of higher education institutions (HEIs) has become more and more popular, there are increasing concerns about the quality of such ranking. In response to such legitimate expectations, in May 2006, the International Ranking Expert Group (IREG) developed and endorsed a guideline document – the Berlin Principles on Ranking of Higher Education Institutions (hereafter called the Berlin Principles), which consist of sixteen descriptive and prescriptive principles for ranking covering four aspects: the purpose and goal of ranking; the design and weighting of indicators; the collection and processing of data; and the presentation of ranking results. The purpose of this paper is to examine selected HEIs rankings according to the Berlin Principles as well as to propose concrete ‘Fourteen Criteria’ which, if followed, could enhance the quality of ranking. 1. The authors would like to acknowledge that research for this paper was partly supported by the National Social Science Foundation of China (Gr...

Comparison of the effect of mean-based method and z-score for field normalization of citations at the level of Web of Science subject categories

Field normalization is a necessary step in a fair cross-field comparison of citation impact. In practice, mean-based method (m-score) is the most popular method for field normalization. However, considering that mean-based method only utilizes the central tendency of citation distribution in the normalization procedure and dispersion is also a significant characteristic, an open and important issue is whether alternative normalization methods which take both central tendency and variability into account perform better than mean-based method. With the aim of collapsing citation distributions of different fields into a universal distribution, this study compares the normalization effect of m-score and z-score based on 236 Web of Science (WoS) subject categories. The results show that both m-score and z-score have remarkable normalization effect as compared with raw citations, but neither of them can realize the ideal goal of “universality of citation distributions”. The results also suggest that m-score is generally preferable to z-score. The essential cause that m-score has an edge over z-score as a whole has a direct relationship with the characteristics of skewed citation distributions in which case m-score is more applicable than z-score.

Academic Ranking of World Universities by Broad Subject Fields.

Upon numerous requests to provide ranking of world universities by broad subject fields/schools/colleges and by subject fields/programs/departments, the authors present the ranking methodologies and problems that arose from the research by the Institute of Higher Education, Shanghai Jiao Tong University on the Academic Ranking of World Universities by Broad Subject Fields (ARWU‐FIELD) in 2006. Using objective indicators and internationally comparable data, the authors ranked five broad subject fields: natural sciences and mathematics (SCI); engineering/technology and computer sciences (ENG); life and agriculture sciences (LIFE); clinical medicine and pharmacy (MED); and social sciences (SOC). 1. Acknowledgment: This research is partly supported by the National Natural Science Foundation of China (Grant number: 70673062)

How World-Class Universities Affect Global Higher Education

World-class universities (WCU), commonly recognized as global research universities or flagship universities, are cornerstone institutions embedded in any academic system and play an important role in developing a nation’s competitiveness in the global knowledge economy.

Building World-Class Universities

World-class universities, commonly referred to as the most prestigious research universities, are essential in developing a nation’s competitiveness in the global knowledge economy. These universities, at the pinnacle of the higher education hierarchy, play key roles in creating and disseminating knowledge, educating a highly skilled workforce for technological and intellectual leadership, and serving the needs of society (Altbach, 2009; Van der Wende, 2009). In the past decade, the development of world-class universities is high on the policy agenda of various stakeholders across the globe (Altbach & Balan, 2007; Huisman, 2008). Various reforms and development strategies at both national and institutional levels have been outlined and observed.

Matching Visibility and Performance

The concept of world-class universities (WCU) has increasingly gained popularity in the past two decades around the world. WCU, often used interchangeably to refer to research universities or flagship universities, are regarded as cornerstone institutions of any academic system and imperative to develop a nation’s competitiveness in the global knowledge economy.

Improving the normalization effect of mean-based method from the perspective of optimization: optimization-based linear methods and their performance

Mean-based method may be the most popular linear method for field normalization of citation impact. However, the relatively good but not ideal performance of mean-based method, plus its being a special case of the general scaling method yxa0=xa0kx and the more general affine method yxa0=xa0kxxa0+xa0b, implies that more effective linear methods may exist. Under the idea of making the citation distribution of each field approximate a common reference distribution through the transformation of scaling method and affine method with unknown parameters k and b, we derived the scaling and affine methods under separate unweighted and weighted optimization models for 236 Web of Science subject categories. While the unweighted-optimization-based scaling and affine methods did not show full advantages over mean-based method, the weighted-optimization-based affine method showed a decided advantage over mean-based method along most parts of the distributions. At the same time, the trivial advantage of weighted-optimization-based scaling method over mean-based method indirectly validated the good normalization performance of mean-based method. Based on these results, we conclude that mean-based method is acceptable for general field normalization, but in the face of higher demands on normalization effect, the weighted-optimization-based affine method may be a better choice.